Overall Equipment Effectiveness of Critical Machines in Manufacturing Industries

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Overall Equipment Effectiveness of Critical Machines in Manufacturing Industries
  Proceedings of the 2 nd  International Conference on Current Trends in Engineering and Management ICCTEM -2014 17 – 19, July 2014, Mysore, Karnataka, India   145   OVERALL EQUIPMENT EFFECTIVENESS OF CRITICAL MACHINES IN MANUFACTURING INDUSTRIES – A PRACTICAL ANALYSIS B.C. Ashok 1 , Dr. T.R. Srinivas 2   1 (Department of Mechanical Engineering, Vidyavardhaka College of Engineering, Mysore, Karnataka, India) 2 (Department of Industrial Production & Engineering, Sri Jayachamarajendra College of Engineering, Mysore, Karnataka, India) ABSTRACT Overall Equipment Effectiveness (OEE) is a measure used in Total Productive Maintenance (TPM), a maintenance program which involves a newly defined concept for maintaining plants and equipment, to calculate the percentage of actual effectiveness of the equipment, taking into consideration the availability of the equipment, the performance rate when running and the quality rate of the manufactured product measured over a period of time (days, weeks or months). The equipment criticality is decided by considering how and how much the equipment affects the production volume and quality. The scale of damage incurred by breakdowns of the equipment is also considered. The purpose of this paper is to assess the application of OEE to evaluate the performance of critical machines and to determine to what extent the TPM implementation affects the OEE. The procedure to estimate OEE has also been presented through numerical examples. A case study was carried out in two large scale industries, one that manufactures Tyres for heavy vehicles and the second an automobile industry that manufactures heavy-duty drive axle assemblies. The data collected for two critical machines over a period of one year are statistically analysed to identify the influence of major losses on OEE. Keywords : Total Productive Maintenance (TPM), Effectiveness, Equipment, Performance 1.   INTRODUCTION Overall Equipment Effectiveness (OEE) being performance measure of Total Productive Maintenance (TPM) could be used to evaluate the performance of critical/key equipments of the manufacturing industry. It reflects the performance of all the equipments in the manufacture line. The goal of TPM is to increase equipment effectiveness so each piece of equipment can be operated to its full potential and maintained at that level. The OEE is a measure of the value added to production through equipment, which is a function of machine availability, performance efficiency and the rate of quality. Overall Equipment Effectiveness is a very simple metric that immediately indicates the current status of a manufacturing process. Somehow it also becomes a multifaceted tool allowing one to understand the effect of the various issues in the manufacturing process and their effect on the entire process. The biggest advantage of OEE is that it allows companies to have separate business functions by applying/using a single, easy-to-understand formula. OEE is by far the most effective benchmarking tool in making sound management decisions. Overall Equipment Effectiveness depends on three parameters: Availability of the equipment, Performance of the equipment and the Quality of the product. It is given by; OEE = Availability Ratio x Performance Ratio x Quality Ratio   INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING AND TECHNOLOGY (IJMET) ISSN 0976 – 6340 (Print) ISSN 0976 – 6359 (Online) Volume 5, Issue 9, September (2014), pp. 145-150 © IAEME: Journal Impact Factor (2014): 7.5377 (Calculated by GISI)   IJMET   © I A E M E    Proceedings of the 2 nd  International Co ã   Availability Ratio - the share of the ac breakdowns will reduce the availabilit of operators. The only time that one m ã   Performance Ratio - Loss of productio when the equipment is not run with full ã   Quality Ratio - the amount of the produ A large scale Tyre manufacturing assemblies automobile industry which has equipments from different sectors of the inBanbury, 4 Roll Calender Machine in Tyr industry by taking readings directly and hen 2.   RELATED WORKS OEE was proposed by Nakajima [ initiatives carried out as part of his propo metric or measure for the evaluation of equipment losses, which include equipment Fig. 1: ã   Equipment failure or breakdown losand quality losses caused by defectiv ã   Set-up and adjustment time losses: production of one item ends and the ã   Idling/minor stop losses: These loss when a machine is idling. ã   Reduced speed losses: These losses speed. ã   Quality defects and rework: Defect/r ã   Reduced yield or Start-up: Reduced An increase in overall equipment can significantly reduce random machine Jayant Rajgopal [2] states that machine bre ference on Current Trends in Engineering and Manage 17 – 19, July 2014, Myso 146   tual production time and the planned production time. ratio, including setup times, preventive maintenance, y choose to deduct from the availability ratio is lack of o due to underutilization of the machinery. In other word speed. Short, unregistered, stops may affect the perform ction that has to be discharged or scrapped. industry which has implemented TPM to full extent partially implemented TPM were selected as case stu ustry were chosen for the study. This paper investigate industry and Straddle Facing, Centerless Grinding Ma ce the performance of equipments is analysed. 1] as an approach to evaluate the progress achieved thro sed total productive maintenance (TPM) philosophy. equipment effectiveness. In considering OEE, Nakaj downtime loss, performance loss, and defect loss as sho ajor losses limiting equipment efficiency es: These losses are categorized as time losses when pro e products. These losses result from downtime and defective prod quipment is adjusted to meet the requirements of anothe es occur when the production is interrupted by a temp refer to the difference between equipment design speed work losses are defined as volume losses due to defects ield/Start-up losses are defined as time losses (output de effectiveness, which is a function of down time and ot breakdowns, in turn, inventory, and lead time. Fawaz kdowns and minor stoppages account for 20–30% of los   ent ICCTEM -2014 re, Karnataka, India   ll planned stops and reakdowns and lack ders. s, losses are incurred nce ratio as well. nd heavy-duty Axle ies and two critical OEE calculation of hine in Automobile gh the improvement e defines OEE as a ima defines six big n in Fig. 1. ductivity is reduced, cts that occur when item. rary malfunction or and actual operating nd rework. line). er production losses A. Abdulmalek and in OEE.  Proceedings of the 2 nd  International Conference on Current Trends in Engineering and Management ICCTEM -2014 17 – 19, July 2014, Mysore, Karnataka, India   147   I.P.S. Ahuja and J.S. Khamba [3] have suggested that OEE is an all-inclusive benchmarking tool that serves to gauge the various subcomponents of the manufacturing process (i.e., availability, performance and quality) and used to measure actual improvements on 5S, Lean Manufacturing, TPM, Kaizen and Six Sigma. Benchmarking overall equipment effectiveness can facilitate an organization to realization of zero breakdown, zero defect, zero machine stoppage, zero accidents, zero pollution, which serve as the ultimate objective of TPM. When using OEE with these management systems the benefits become tangible and noteworthy. Ron and J.E. Rooda [4] have stated that, manufactured goods are a result of a complex production process and without the proper measuring tools and formula, the business can be expected to run blindly even in the light of day. Having the right metrics, OEE provides a window to analyse out-of-the-ordinary issues and gives an established framework for improving the entire manufacturing process. They further announce that a key performance measure in mass production environments is OEE. Bulent Dal et al. [5], suggest that the OEE measure can be applied at several different levels within a manufacturing environment. Firstly, OEE can be used as a “benchmark”' for measuring the initial performance of a manufacturing plant in its entirety. In this manner the initial OEE measure can be compared with future OEE values, thus quantifying the level of improvement made. Secondly, an OEE value, calculated for one manufacturing line, can be used to compare line performance across the factory, thereby highlighting any poor line performance. Thirdly, if the machines process work individually, an OEE measure can identify which machine performance is worst, and therefore indicate where to focus TPM resources. Christian N. Madu [6] shows that equipment maintenance and reliability management are importantly associated with an organization’s competitiveness and must be given adequate attention in the organization's strategic planning. OEE is an effective way of analysing the efficiency of a single machine or an integrated machinery system. However, Alok Mathur et al. [7] implies that the most important objective of OEE is not to get an optimum measure, but to get a simple measure that tells production personnel where to spend their improvement resources. The greatest contribution of OEE is that it is a simple, but still comprehensive, measure of internal efficiency and that it can work as an important indicator of the continuous improvement process. 3.   OVERALL EQUIPMENT EFFECTIVENESS (OEE) MEASUREMENT In this section, the measurement of OEE for the selected critical equipments is presented. OEE combines the operation, maintenance and management of manufacturing equipment and resources. It takes the most common and important sources of productivity loss, which are called six big losses, shown in Fig. 1. These losses are quantified as Availability (A), Performance (P) and Quality (Q) in order to estimate OEE and OEE calculation is given by: OEE = Availability × Performance × Quality According to Nakajima [1] the ideal conditions are: Availability…..greater than 90%, Performance Efficiency…… greater than 95%, Rate of Quality products …… greater than 99%. Therefore, the ideal OEE should be 85+ %. However, literature survey indicates that the exact definition of OEE differs between applications and various authors. For an organization, wishing to measure their OEE, the differences in various approaches of calculating OEE parameters (A, P, Q) could be significant in terms of OEE resultant figures. 3.1   Tyre industry 3.1.1   Banbury Failure Loss (in %): 1.782931 (1) Set up & Adjustment Loss (in %): 1.59 (2) Shut down Loss (in %): 0.638346123 (3) Minor stoppage & Idle Loss (in %): 0.02329558 (4) Management Loss (in %): 0.07 (5) 17909.995)5()4()3()2()1( 100  =++++ −= ty Availabili  Line Organization Loss (in %): 0.71 (6) Measurement Loss (in %): 0.098141 (7) 594.992)7()6( 100  =+−= ePerformanc  Defect & Rework Loss (in %): 6.18 (8) Quality  = 100 – (8) = 93.82 󰁏󰁅󰁅  󰀱󰀰󰀰  󰀮   󰁘 󰀮  󰁘 󰀮   󰀹󰀰󰀮󰀷󰀳󰀷󰀥    Proceedings of the 2 nd  International Conference on Current Trends in Engineering and Management ICCTEM -2014 17 – 19, July 2014, Mysore, Karnataka, India   148   3.1.2   4 Roll Calender Machine Failure Loss (in %): 1.729443 (1) Set up & Adjustment Loss (in %): 0.7791 (2) Shut down Loss (in %): 0.31279 (3) Minor stoppage & Idle Loss (in %): 0.046358 (4) Management Loss (in %): 0.0343 (5) 41926.995)5()4()3()2()1( 100  =++++ −= ty Availabili  Measurement Loss (in %): 0.0481 (6) Performance  = 100 – (6) = 99.95 Defect & Rework Loss (in %): 4.4344 (7) Quality  = 100 – (7) = 95.57   󰀱󰀰󰀰 󰀮    󰀮   󰀮   󰀹󰀰󰀮󰀵󰀰󰀥   3.2   Automobile industry 3.2.1   Straddle Facing Setup Time (in Hours): 15.1 Breakdown (in Hours): 2.00 SetupTime BreakdownsetupTimety Availabili  −= 86.01.1521.15 =−=  Run Rate (in Hours): 2688 Ideal Run Rate (in Hours): 3262.5 82.05.32622688 === SetupTime RunrateePerformanc  Production Output (actual): 155 Production Output (Target): 180 86.0180155)arg()( === et T sTotalPiece  ActualGoodPiecesQuality  OEE = 0.86 X 0.82 X 0.86 X 100 = 60.64% 3.2.2   Centerless Grinding Setup Time (in Hours): 35 Breakdown (in Hours): 4.00 SetupTime BreakdownsetupTimety Availabili  −=   88.035435 =−=  Run Rate (in Hours): 2368 Ideal Run Rate (in Hours): 2880 82.028802368 === SetupTime RunrateePerformanc  Production Output (actual): 138 Production Output (Target): 160 86.0160138)arg()( === et T sTotalPiece  ActualGoodPiecesQuality  OEE = 0.88 X 0.82 X 0.86 X 100 = 62.05% 4.   ANALYSIS OF RESULTS FOR OEE This section presents the overall profile of the samples, descriptive statistics and frequency distribution. The results of statistical methods of descriptive statistics, One way Anova, Scheffe’s post hoc test are tabulated in Table 1. Here we have grouped the machines with similar criticality as Machine 1 and Machine 2. Hence Banbury of Tyre industry and Straddle Facing of Automobile industry fall under Machine 1 and 4 Roll Calender Machine of Tyre industry and Centerless Grinding of Automobile industry fall under Machine 2.

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